“highly significant”

A strong and highly significant positive correlation was identified between handler substitution (Handler) and both serum cortisol levels (r s = 0.67, p = 0.001) and respiratory rate (r s = 0.66, p = 0.001), linking personnel rotation to heightened physiological stress.

Non-metric Multidimensional Scaling (NMDS) further revealed highly significant differences in community structure among the different zones of the Xiaolangdi Reservoir (R = 0.7466, p < 0.001; Figure S4A ).

A highly significant association was found for protein intake ( p < 0.001), with a very large effect size (Cramer’s V = 0.58).

65.49%), a difference that was highly significant (χ 2 = 16.287, p < 0.001, Cramer’s V = 0.217, Power = 0.981).

Moreover, IFI44L exhibited highly significant positive correlations with both XAF1 and MX1 in SLE patients (r = 0.21, 0.18, all p < 0.001) ( Figure 3 a).

According to the analysis results, highly significant positive correlations were found between the total burnout score and the subscales of emotional exhaustion (ρ = 0.909; p = 0.001) and depersonalization (ρ = 0.734; p = 0.001).

After adjustment, this association remained highly significant, with an adjusted OR of 0.180 (95% CI: 0.090–0.362, p < 0.001).

Association with Blood Product Type and Post-Transfusion Workup PRBC transfusion was the blood product most associated with ATRs (196, 82.4%), with a highly significant association across all reaction types ( p < 0.001).

In contrast, on attenuation of fat mass, treatment with 5 mg/kg/day bisoprolol and 1.7 μg/kg/day ARA 284 showed highly significant effects compared with the placebo ( p < 0.001 vs. placebo, respectively).

Patients demonstrated a significant reduction in high-risk categorization (β = −0.777, p < 0.001) and low-risk categorization (β = −0.597, p = 0.007), with the overall effect of measurement time being highly significant (Wald χ 2 = 10.624, p = 0.001).

Statistical analysis demonstrated a highly significant difference in the numerical areal density of HBCs between trimesters ( p < 0.001) ( Table 2 ).

One-third of thrombus cases occurred in patients treated with warfarin, a finding that remained highly significant (p < 0.001).

Notably, when lactate was included, glucose lost its independent significance ( p = 0.233), while lactate remained highly significant (OR = 1.83, p < 0.001), suggesting that lactate captures metabolic derangement more effectively than glucose in a comprehensive model. 3.4.

Internal Validation and Model Diagnostics The multivariable binomial logistic regression model constructed to evaluate 12-month mortality demonstrated an excellent overall fit (Deviance = 358, AIC = 370, BIC = 393, McFadden’s R 2 = 0.228) and was statistically highly significant (Omnibus likelihood ratio test χ 2 = 106, df = 5, p < 0.001).

Zone-specific analysis revealed highly significant differences in coverage across anatomical regions (Friedman chi2 = 450.12, p < 0.001).

The “Edge Effect” and the Bio-Morphological Vulnerability of the Host The highly significant statistical differences revealed by the Kruskal–Wallis test ( p < 0.001) highlight the crucial role of stand structure and habitat fragmentation in mediating the population dynamics of C. arcuata .

The overall log-rank test indicated a highly significant difference between groups (χ 2 = 112.14, p < 0.001).

The GLM analysis revealed highly significant effects of isolate, pruning wound age, and their interaction for each cultivar ( p < 0.001 for all factors), indicating that lesion length was influenced by both factors and their interaction ( Table 1 ).

Two-way ART ANOVA revealed highly significant main effects for both print orientation ( p < 0.001, η 2 p = 0.9512) and conditioning/aging ( p < 0.001, η 2 p = 0.5052), both with large effect sizes ( Table 3 ).

Notably, calendar period was itself a highly significant prognostic factor (HR: 0.217, 95% CI: 0.145–0.326, p < 0.001), reflecting substantially improved outcomes in the more recent era.

A highly significant association was observed between AIDA class and delivery outcome (χ 2 (4) = 57.49, p < 0.001), with a very large effect size (Cramer’s V = 0.853) and a strong monotonic relationship (Spearman’s ρ = 0.738, p < 0.001).

One-way ANOVA among groups treated only with Kloroben mouthrinse showed highly significant differences in color stability between materials (F = 221.300; p < 0.001).

Multiple SF-36 subscale factors, such as SF-36 PF, SF-36 RP, SF-36 BP, and SF-36 RE, showed highly significant differences between groups for both MCS and PCS improvements (all p <0.001).

In Group A, a strong and highly significant positive correlation was observed between the coronal and middle thirds (r = 0.869, p = 0.001), indicating specimens with higher coronal temperatures also showed proportionally higher middle-third temperatures—consistent with a predictable, monotonic thermal decay model.

Although this design introduces within-tooth correlation for the adhesive type factor, the two specimens from each tooth were assigned to different adhesive types; consequently, any residual within-tooth correlation would be expected to act conservatively on the adhesive type comparison, reducing rather than inflating the F-statistic, and is therefore unlikely to account for the observed highly significant effect (F = 33.345, p < 0.001).